PROJECT 3 -ABSTRACT We propose to use advanced computational methods to understand the causes & dynamics of SIV rebound in macaques. This project is a part of an overall program that combines extensive experimental work in SIV-infected macaques with quantitative analysis and computational models to provide a common framework to understand viral rebound following the cessation of antiretroviral therapy (ART) in suppressed macaques. The connections to HIV are clear, and will be enhanced by the parallel development and comparison of experimental-data-based computational models of SIV in macaques and HIV in humans. Clinical relevance is further enhanced by the use of the developed models to simulate many different therapeutic approaches to find methods to delay or eliminate viral rebound. As part of the overall Program, Project 3 (?Quantitative analysis and computational modeling of viral rebound?) will perform quantitative data analysis of all experimental data from the projects and cores of the Program, identify biomarkers across multiple data sources that are predictive of viral rebound, and develop and validate a predictive computational model with parameters specific to macaques and SIV. Projects 1 and 2 and the BSL3 core will conduct experiments with quantitative readouts of many different types including: gene expression, chemokine/cytokine expression, immune cell metrics, viral reservoir characterization, and the viral load in both the plasma and CSF. These measurements will be made at multiple time points, including during active infection, suppression by ART, release from suppression by cessation of ART, and post-cessation viral rebound. The careful and thorough analysis of data proposed in this project will not just provide a service to the other projects, but also enable synthesis and integration of data across all the projects. This will aid the Program in developing a rigorous, system-level understanding of viral rebound. In order to accomplish this, we have identified five goals for Project 3: (a) to provide quantitative analysis of the multimodal, diverse data within each project and across projects; (b) to build a mechanistic computational model that integrates this data; (c) to assist in experimental design, selecting appropriate experimental conditions by analyzing previous data; (d) to identify biomarkers of viral rebound; and (e) to translate this SIV-in-macaque study and its insights to HIV in humans by comparing our mechanistic computational models of SIV to our models of HIV. These goals have been incorporated and distilled into three aims for Project 3: (1) Understand the dynamics of viral rebound using longitudinal data. (2) Identify pre- and early post-cessation biomarkers of viral rebound. (3) Predict rebound- targeting therapeutic interventions in SIV and HIV.